grabba 0.0.4

Python SDK for Grabba API

Grabba Python SDK

Grabba Python SDK provides a simple and intuitive interface for scheduling web data extraction jobs, retrieving job results, and managing your extraction workflows. All SDK types are now implemented as Pydantic BaseModels for full JSON compatibility and built-in validation.

Installation

Install the SDK using pip:

pip install grabba

Basic Setup

Import the Client and Required Types

from grabba import Grabba, Job, JobNavigationType, JobSchedulePolicy, JobTaskType

Note: All types such as Job, JobTask, etc., are now Pydantic BaseModels. This means that they support methods like .model_dump() and .json() for serialization, and Enum fields are automatically converted to their literal values during JSON encoding.

Initialize a Client Instance

grabba = Grabba(api_key="your-api-key", region="US")  # Optional: Defaults to US

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Methods

extract

extract(job: Job) -> Dict

Schedules a new web data extraction job.

Parameters:

• job: A Job object containing the extraction configuration.

Returns:

• A dictionary containing the response status, message, and job_result.

Example:

from grabba import Job, JobSchedulePolicy, JobNavigationType, JobTaskType

job = Job(
    url="https://docs.grabba.dev/home",
    schedule={
        "policy": JobSchedulePolicy.IMMEDIATELY  # Enum values will be serialized as literals
    },
    navigation={
        "type": JobNavigationType.NONE
    },
    tasks=[{
        "type": JobTaskType.WEB_PAGE_AS_MARKDOWN,
        "options": {"only_main_content": True}
    }],
)

# Note: Since Job is a Pydantic model, you may also print its JSON representation:
print(job.json())

response = grabba.extract(job)
print(f"Job completed with status: {response['status']}")

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schedule_job

schedule_job(job_id: str) -> Dict

Schedules an existing job for execution.

Parameters:

• job_id: The ID of the job to schedule.

Returns:

• A dictionary containing the response status, message, and job_result.

Example:

response = grabba.schedule_job("12345")
print(f"Job completed with status: {response['status']}")

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get_jobs

get_jobs() -> GetJobsResponse

Retrieves a list of all jobs associated with the API key.

Returns:

• A list of Job objects.

Example:

jobs = grabba.get_jobs()
for job in jobs:
    print(job.model_dump())

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get_job

get_job(job_id: str) -> GetJobResponse

Retrieves details of a specific job by its ID.

Parameters:

• job_id: The ID of the job to retrieve.

Returns:

• A JobDetail object containing job details.

Example:

job = grabba.get_job("12345")
print(job.model_dump())

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get_job_result

get_job_result(job_result_id: str) -> JobResult

Retrieves the results of a specific job by its result ID.

Parameters:

• job_result_id: The ID of the job result to retrieve.

Returns:

• A JobResult object.

Example:

result = grabba.get_job_result("67890")
print(result.model_dump())

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delete_job (New in 0.0.4)

delete_job(job_id: str) -> Dict

Deletes a specific job by its ID.

Parameters:

• job_id: The ID of the job to delete.

Returns:

• A dictionary containing the response status and message.

Example:

response = grabba.delete_job("12345")
print(f"Job deletion status: {response['status']}")

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Error Handling

The SDK throws errors for:

• Invalid API keys
• Failed API requests
• Missing or invalid parameters

Example:

try:
    response = grabba.extract(job)
    if response["status"] == "success":
        print("Results data:", response["job_result"]["data"])
    else:
        print("Error message:", response["message"])
except Exception as err:
    print("Error:", err)

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Contributing

Contributions are welcome! Please open an issue or submit a pull request on GitHub.

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License

This project is licensed under the MIT License. See the LICENSE file for details.

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Additional Notes

• Pydantic Serialization:
  All SDK models are now Pydantic BaseModels, so you can use .json() or .model_dump() to serialize your models with Enums automatically converted to their literal values.
• Enum Configuration:
  In our BaseModels, we use json_encoders in the Config class to ensure Enum fields (such as JobSchedulePolicy and JobTaskType) are output as their literal values.
• Type Safety:
  With Pydantic, all input data is validated against the model definitions, which helps catch errors early.

Feel free to adjust these examples as needed, and let us know if you have any questions or further changes!

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Change Log

Version 0.0.4 (Latest)

• Improved Job Task Handling: Enhanced task validation and error handling for better reliability.
• New API Method - ``: Now you can delete jobs using their job_id.
• Performance Optimizations: Improved response times by optimizing API requests and serialization.
• Bug Fixes: Fixed minor serialization issues with nested Pydantic models.
• Added delete_job(job_id: str) -> BaseResponse
• Added delete_job_result(job_result_id: str) -> BaseResponse

Version 0.0.3

• Pydantic Integration: All SDK types are now Pydantic BaseModels, enabling JSON serialization and validation.
• Enum Field Optimization: Enums are automatically serialized to their literal values.
• Better Error Handling: More descriptive error messages and improved exception handling.